The present invention relates to a hierarchical model predictive control system, and more particularly to a model predictive control system for calculating a manipulation variable on the basis of a prediction of a prospective motion corresponding to a control on the basis of dynamic characteristics model of a control object.
In recent years, a model predictive control apparatus is often used in a field of process control. The model predictive control apparatus has many characteristics as follows:
(a) it is possible to realize a stable control response against a control object having a long dead-time; PA1 (b) it is possible to improve a following-up by a feed forward control using a prospective reference value; PA1 (c) it is possible to apply for a multivariable control system; PA1 (d) it is possible to easily construct a control system from, for example, a step response which does not need a dynamic characteristics model having an exact control object; PA1 (e) it is possible to precisely control an object by including a physical law and non-linear characteristics of a plant in the predictive model; and PA1 (f) it is possible to directly enter restriction conditions such as upper and lower limits and a change rate limiter with respect to operation of the control object, into a control side. PA1 (1) Nishitani: A practical application, measurement and control for a model predictive control, Journal of the Society of Instrument and Control Engeneers, Vol.28, No.11, pp.996-1004 (1989); and PA1 (2) D. W. Clarke & C. Mohtadi: Properties of Generalized Predictive Control, Automatica (issued by International Federation of Automatic Control), Vol.25, No.6, p.859 (1989). PA1 i) First, since a calculation load is large and a control cycle can not shorten because the model predictive control apparatus repeats a predictive calculation and an optimizing calculation at every control cycle, it is convenient to allot a control having a fast time constant such as a fluid amount control in a process control to the DCS capable of shorten a control cycle because a load is light; and PA1 ii) Second, since the model predictive control apparatus treats a plurality of a manipulation variable and process variable, there is much probability of a stop of function caused by a trouble in a part of sensors. Accordingly, if there is a lower system such as the DCS, when the upper model predictive control apparatus stops, a stability of the plant is kept to secure a practical use of the plant.
There have already been provided a plurality of predictive control systems which are disclosed in some documents as follows:
Especially in the document (2), there is proposed a generalized predictive control (GPC) system including various model predictive systems. The GPC system is a system that, when a prospective reference value y.sup.* is supplied, a control response prospective value [y(k+i); i=1, . . . , N.sub.D ] is predicted on the basis of a model of a process or a control object, and a manipulation variable increased value .DELTA.U (k) for causing a performance function J showing a control request to be the minimum value is obtained by the following equation (1): ##EQU1##
Here, .parallel.x.parallel. shows a norm of the vector x.
A model predictive apparatus using the GPC system is shown in official gazettes such as Japanese patent application laid-open No. 4-118703 and No. 4-256102.
Generally, a control apparatus of a large scale plant such as a petrochemistry plant, steel plant and electric power plant, is controlled by a decentralized control system (hereafter, abbreviated in DCS) which is usually constructed by a plurality of proportion (P), integral (I) and differential (D) controller. When the plant is connected to the model predictive control apparatus, the model predictive control apparatus as an upper system is connected to the DCS as a lower system by a transmission line such as a data bus and a local area network (LAN) so as to control by transmitting a manipulation variable which is predictively calculated, from the model predictive control apparatus to the DCS. The followings are reasons:
On the other hand, the DCS generally has three control modes, namely, a manual (M) mode, automatic (A) mode and a cascade (C) mode. The M mode shows a case that a loop of the DCS is an open loop, the A mode shows a case that the loop of the DCS has a constant set point value or the loop is a closed loop, and the C mode shows a case that loop of the DCS has a variable set point value in the closed loop.
As described above, in the conventional hierarchical model predictive control system for performing by using the upper model predictive control apparatus and the lower DCS, the model predictive control apparatus performs a model prediction by using a manipulation variable signal of the apparatus as a set point value signal for the DCS without consideration of the control mode of the DCS. Therefore, in the case that the upper model predictive control apparatus operates the set point value of the loop, or that the operator intentionally changes the set point value of the DCS in the A mode in spite of the closed loop condition of the DCS, a influence thereof is not considered in the predictive calculation in the upper model predictive control apparatus, thereby resulting a problem that the manupulation variable is improper, which is obtained by the predictive calculation by the model predictive control apparatus.